LEARNING CURVE OF FUSION MRI-TARGETED PROSTATE BIOPSY AND 3D-TRUS SEGMENTATION - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue BJU International Année : 2024

LEARNING CURVE OF FUSION MRI-TARGETED PROSTATE BIOPSY AND 3D-TRUS SEGMENTATION

Résumé

Objective To report the learning curve of multiple operators for fusion magnetic resonance imaging (MRI) targeted biopsy and to determine the number of cases needed to achieve proficiency. Materials and Methods All adult males who underwent fusion MRI targeted biopsy between February 2012 and July 2021 for clinically suspected prostate cancer (PCa) in a single centre were included. Fusion transrectal MRI targeted biopsy was performed under local anaesthesia using the Koelis platform. Learning curves for segmentation of transrectal ultrasonography (TRUS) images and the overall MRI targeted biopsy procedure were estimated with locally weighted scatterplot smoothing by computing each operator's timestamps for consecutive procedures. Non‐risk‐adjusted cumulative sum (CUSUM) methods were used to create learning curves for clinically significant (i.e., International Society of Urological Pathology grade ≥ 2) PCa detection. Results Overall, 1721 patients underwent MRI targeted biopsy in our centre during the study period. The median (interquartile range) times for TRUS segmentation and for the MRI targeted biopsy procedure were 4.5 (3.5, 6.0) min and 13.2 (10.6, 16.9) min, respectively. Among the 14 operators with experience of more than 50 cases, a plateau was reached after 40 cases for TRUS segmentation time and 50 cases for overall MRI targeted biopsy procedure time. CUSUM analysis showed that the learning curve for clinically significant PCa detection required 25 to 45 procedures to achieve clinical proficiency. Pain scores ranged between 0 and 1 for 84% of patients, and a plateau phase was reached after 20 to 100 cases. Conclusions A minimum of 50 cases of MRI targeted biopsy are necessary to achieve clinical and technical proficiency and to reach reproducibility in terms of timing, clinically significant PCa detection, and pain.
Fichier principal
Vignette du fichier
version-finale-auteurs.pdf (795.63 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04580995 , version 1 (21-05-2024)

Identifiants

Citer

Louis Lenfant, Clément Beitone, Jocelyne Troccaz, Morgan Rouprêt, Thomas Seisen, et al.. LEARNING CURVE OF FUSION MRI-TARGETED PROSTATE BIOPSY AND 3D-TRUS SEGMENTATION. BJU International, 2024, 133 (6), pp.709-716. ⟨10.1111/bju.16287⟩. ⟨hal-04580995⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More